{"id":20304373,"url":"https://github.com/dev-michael-schmidt/eyeball-sam","last_synced_at":"2025-07-08T01:12:34.193Z","repository":{"id":106652912,"uuid":"593452892","full_name":"dev-michael-schmidt/eyeball-sam","owner":"dev-michael-schmidt","description":"A home grown real-time object dectecion for embedded devices using YOLOv7 ","archived":false,"fork":false,"pushed_at":"2024-07-02T15:32:58.000Z","size":38400,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-03-04T07:13:52.499Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/dev-michael-schmidt.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-01-26T02:43:59.000Z","updated_at":"2024-07-02T15:32:56.000Z","dependencies_parsed_at":"2025-01-14T11:14:14.871Z","dependency_job_id":"4525e8be-e3a7-441a-8f35-ec7b72b97cd4","html_url":"https://github.com/dev-michael-schmidt/eyeball-sam","commit_stats":null,"previous_names":["michaelschmidt82/small-eyeballs","dev-michael-schmidt/eyeball-sam"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/dev-michael-schmidt/eyeball-sam","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dev-michael-schmidt%2Feyeball-sam","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dev-michael-schmidt%2Feyeball-sam/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dev-michael-schmidt%2Feyeball-sam/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dev-michael-schmidt%2Feyeball-sam/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/dev-michael-schmidt","download_url":"https://codeload.github.com/dev-michael-schmidt/eyeball-sam/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dev-michael-schmidt%2Feyeball-sam/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":264172129,"owners_count":23567822,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-14T16:44:00.380Z","updated_at":"2025-07-08T01:12:34.159Z","avatar_url":"https://github.com/dev-michael-schmidt.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# eyeball-sam\n![](https://github.com/MichaelSchmidt82/eyeball-sam/blob/main/content/cool_demo.gif)\n\n**What:**  Real-time object detection, person detection, and face recognition using YOLOv7 in TensorFlow Lite targeted for devices at the edge with Google Coral hardware.\n\n## Requirements:\n### Software\n- 🖥️ Ubuntu 20.04\n- 🐍️ Python 3.8\n- 📦️ See requirements.txt, there are a lot.\n- 📷️ It is recommend to ~[build OpenCV from source](https://docs.opencv.org/4.x/d7/d9f/tutorial_linux_install.html) for local testing (or just in general).~ use the requirements.txt version.\n### Hardware\n- 🌊️ [Google Coral](https://coral.ai/). They have low-wattage USB and M.2 TPUs. A must for real-time video processing.\n\nUsage:\n1. Create a virtual environment and `pip install -r requirements.txt`.\n2. Run the `create_tf_lite.ipynb` notebook to download use the model weights. This notebook will convert ONNX format to tf-lite.\n3. Run `tfl_yolov7_main.py`.\n\nNote: by default, openCV will use your wedcam (`cv2.VideoCapture(0)`)\n\nThis project was updated on 01/29/2024\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdev-michael-schmidt%2Feyeball-sam","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdev-michael-schmidt%2Feyeball-sam","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdev-michael-schmidt%2Feyeball-sam/lists"}